# Week 2 Quiz - couldn't figure out why an answer is right or wrong

I wish that answers in quizzes were explained, why an answer is right or wrong… I looked over the course notes and did additional google searches to try to understand what concept I’m missing. But I’m having a hard time finding notes related to specific questions. I even went back and reviewed all the videos one more time, and am still not learning what I need to pass the quiz.

For example, questions like how to vectorize a for loop, the lecture notes examples are in the form of z = np.dot(w.T,X) + b while the multiple choice answers are in the form of c = a + b.T . Where’s this disconnect coming from?

Another question about “logistic loss”, I referenced both Logistic_Regression.pdf and Logistic_Regression_Cost_Function.pdf, made a couple of wrong understanding of those notes, and still couldn’t figure out how value of y hat and y relates to logistic loss.

Is there a different way to approach learning through this course/ week?

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The questions about c = a + b.T and the like are not related to the specific equations and formulas we have for logistic regression and neural networks. It’s just testing your understanding of the meaning of the various types of vector operations. You just have to draw yourself a picture of what is happening in the loop and then try to map that to the equivalent vector operations.

For the log loss question, I hope we cleared that up in our side DM conversation. The main takeaway is to remember that all the logarithms here are natural logs, not logs base 10. The notation is different in the ML world than in the math world and we just have to realize that and “deal with it”.

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